{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model: XGBoost"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Importing Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import _pickle as pickle\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import precision_score, recall_score, accuracy_score, f1_score, confusion_matrix, classification_report\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loading in Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_excel('../top10_features.xlsx')\n",
    "df = df.drop(df.columns[0], axis = 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scaling the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "scaler = StandardScaler()\n",
    "\n",
    "features_df = df.drop([\"Decision\"], 1)\n",
    "\n",
    "scaled_df = pd.DataFrame(scaler.fit_transform(features_df), \n",
    "                               index=features_df.index, \n",
    "                               columns=features_df.columns)\n",
    "\n",
    "df = scaled_df.join(df.Decision)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Splitting the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df.drop([\"Decision\"], 1)\n",
    "y = df.Decision\n",
    "\n",
    "# Train, test, split\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Helper Functions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Function for plotting confusion matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_confusion_matrix(y_true, y_pred, labels=[\"Sell\", \"Buy\", \"Hold\"], \n",
    "                          normalize=False, title=None, cmap=plt.cm.coolwarm):\n",
    "\n",
    "    cm = confusion_matrix(y_true, y_pred)\n",
    "    fig, ax = plt.subplots(figsize=(12,6))\n",
    "    im = ax.imshow(cm, interpolation='nearest', cmap=cmap)\n",
    "    ax.figure.colorbar(im, ax=ax)\n",
    "    # We want to show all ticks...\n",
    "    ax.set(xticks=np.arange(cm.shape[1]),\n",
    "           yticks=np.arange(cm.shape[0]),\n",
    "           # ... and label them with the respective list entries\n",
    "           xticklabels=labels, yticklabels=labels,\n",
    "           title=title,\n",
    "           ylabel='ACTUAL',\n",
    "           xlabel='PREDICTED')\n",
    "    # Rotate the tick labels and set their alignment.\n",
    "    plt.setp(ax.get_xticklabels(), rotation=45, ha=\"right\",\n",
    "             rotation_mode=\"anchor\")\n",
    "    # Loop over data dimensions and create text annotations.\n",
    "    fmt = '.2f' if normalize else 'd'\n",
    "    thresh = cm.max() / 1.5\n",
    "    for i in range(cm.shape[0]):\n",
    "        for j in range(cm.shape[1]):\n",
    "            ax.text(j, i, format(cm[i, j], fmt),\n",
    "                    ha=\"center\", va=\"center\",\n",
    "                    color=\"snow\" if cm[i, j] > thresh else \"orange\",\n",
    "                    size=26)\n",
    "    ax.grid(False)\n",
    "    fig.tight_layout()\n",
    "    return ax"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Modeling\n",
    "The preferred evaluation metric used will be __Precision__ for each class.  They will be optimized using the __F1 Score-Macro-Average__ to balance the Precision and Recall.  This is done because we want to not only be correct when predicting but also make a decent amount of predictions for each class.  Classes such as 'Buy' and 'Sell' are more important than 'Hold'."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fitting and Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Preventing error from occuring: XGBoost causes kernel to die.\n",
    "import os\n",
    "os.environ['KMP_DUPLICATE_LIB_OK']='True'\n",
    "from xgboost import XGBClassifier\n",
    "import xgboost as xgb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n",
       "              colsample_bynode=1, colsample_bytree=1, gamma=0,\n",
       "              learning_rate=0.1, max_delta_step=0, max_depth=3,\n",
       "              min_child_weight=1, missing=None, n_estimators=100, n_jobs=1,\n",
       "              nthread=None, objective='multi:softprob', random_state=0,\n",
       "              reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,\n",
       "              silent=None, subsample=1, verbosity=1)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Instatiating the model classifier\n",
    "clf = xgb.XGBClassifier()\n",
    "\n",
    "# Fitting to the Data\n",
    "clf.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Printing out Evaluation Metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "        Sell       0.25      0.20      0.22         5\n",
      "         Buy       0.64      0.70      0.67        10\n",
      "        Hold       0.50      0.50      0.50         2\n",
      "\n",
      "    accuracy                           0.53        17\n",
      "   macro avg       0.46      0.47      0.46        17\n",
      "weighted avg       0.51      0.53      0.52        17\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Classifier predictions\n",
    "pred = clf.predict(X_test)\n",
    "\n",
    "#Printing out results\n",
    "report = classification_report(y_test, pred, target_names=['Sell', 'Buy', 'Hold'])\n",
    "print(report)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Confusion Matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_confusion_matrix(y_test, pred, title=\"Confusion Matrix\")\n",
    "np.set_printoptions(precision=1)\n",
    "# Plot non-normalized confusion matrix\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tuning Model Parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GridSearchCV"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Parameters to tune\n",
    "params = {\"booster\": [\"gbtree\", \"gblinear\", 'dart'],\n",
    "          \"eta\": [.1, .3, .6, .9],\n",
    "          \"gamma\": [0, 1, 10],\n",
    "          \"n_estimators\": [50, 100, 200],\n",
    "          \"max_depth\": [1, 3, 6],\n",
    "          \"grow_policy\": ['depthwise', 'lossguide']}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 3 folds for each of 648 candidates, totalling 1944 fits\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.844, test=0.262), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.832, test=0.394), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.895, test=0.317), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.943, test=0.217), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.966, test=0.392), total=   0.0s"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.\n",
      "C:\\Users\\72445\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1437: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples.\n",
      "  'precision', 'predicted', average, warn_for)\n",
      "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s remaining:    0.0s\n",
      "[Parallel(n_jobs=1)]: Done   2 out of   2 | elapsed:    0.0s remaining:    0.0s\n",
      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    0.0s remaining:    0.0s\n",
      "[Parallel(n_jobs=1)]: Done   4 out of   4 | elapsed:    0.1s remaining:    0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.913, test=0.317), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=1.000, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=1.000, test=0.455), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.982, test=0.359), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.165), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.294), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.435), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.170), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.482), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.435), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.482), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.435), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.199), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.349), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.522), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.194), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.542), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.466), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.241), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.542), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.466), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.844, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.832, test=0.394), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.895, test=0.317), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.943, test=0.217), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.966, test=0.392), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.913, test=0.317), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=1.000, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=1.000, test=0.455), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.982, test=0.359), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.165), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.294), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.435), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.170), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.482), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.435), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.482), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.435), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.199), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.349), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.522), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.194), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.542), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.466), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.241), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.542), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.466), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.720, test=0.328), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.558, test=0.318), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.549, test=0.190), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.558, test=0.318), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.749, test=0.262), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.828, test=0.185), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.892, test=0.308), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.875, test=0.308), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.911, test=0.290), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.828, test=0.146), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.928, test=0.341), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.892, test=0.404), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.828, test=0.146), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.828, test=0.146), total=   0.2s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.720, test=0.328), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.558, test=0.318), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.549, test=0.190), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.558, test=0.318), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.828, test=0.185), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.892, test=0.308), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.828, test=0.185), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.911, test=0.290), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.828, test=0.146), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.928, test=0.341), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.892, test=0.404), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.828, test=0.146), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.828, test=0.146), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.204, test=0.202), total=   0.4s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.205, test=0.200), total=   0.3s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.201, test=0.208), total=   0.2s\n",
      "[CV] booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.205, test=0.200), total=   0.3s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.844, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.832, test=0.394), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.895, test=0.317), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.943, test=0.217), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.966, test=0.392), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.913, test=0.317), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=1.000, test=0.455), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.982, test=0.359), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.165), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.294), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.435), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.170), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.482), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.435), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.482), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.435), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.199), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.349), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.522), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.194), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.542), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.466), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.241), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.542), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.466), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.844, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.832, test=0.394), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.895, test=0.317), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.943, test=0.217), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.966, test=0.392), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.913, test=0.317), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=1.000, test=0.200), total=   0.2s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=1.000, test=0.455), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.982, test=0.359), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.165), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.294), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.435), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.170), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.482), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.435), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.482), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.435), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.199), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.349), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.522), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.194), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.542), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.466), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.241), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.542), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.466), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.720, test=0.328), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.558, test=0.318), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.558, test=0.318), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.749, test=0.262), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.828, test=0.185), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.892, test=0.308), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.828, test=0.185), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.911, test=0.290), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.828, test=0.146), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.928, test=0.341), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.828, test=0.146), total=   0.2s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.828, test=0.146), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.720, test=0.328), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.558, test=0.318), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.549, test=0.190), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.558, test=0.318), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.828, test=0.185), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.892, test=0.308), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.875, test=0.308), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.911, test=0.290), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.875, test=0.308), total=   0.1s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.828, test=0.146), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.928, test=0.341), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.892, test=0.404), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.828, test=0.146), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.828, test=0.146), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.205, test=0.200), total=   0.3s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.844, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.832, test=0.394), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.895, test=0.317), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.943, test=0.217), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.966, test=0.392), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.913, test=0.317), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=1.000, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=1.000, test=0.455), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.982, test=0.359), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.165), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.294), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.435), total=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.170), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.482), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.435), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.482), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.435), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.199), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.349), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.522), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.194), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.542), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.466), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.241), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.542), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.466), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.844, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.832, test=0.394), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.895, test=0.317), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.943, test=0.217), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.966, test=0.392), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.913, test=0.317), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=1.000, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=1.000, test=0.455), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.982, test=0.359), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.165), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.294), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.435), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.170), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.482), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.435), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.482), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.435), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.199), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.349), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.522), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.194), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.542), total=   0.1s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.466), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.241), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.542), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.466), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.720, test=0.328), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.558, test=0.318), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.749, test=0.262), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.549, test=0.190), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.558, test=0.318), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.749, test=0.262), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.828, test=0.185), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.892, test=0.308), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.911, test=0.290), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.828, test=0.146), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.928, test=0.341), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.892, test=0.404), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.828, test=0.146), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.828, test=0.146), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.720, test=0.328), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.558, test=0.318), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.549, test=0.190), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.558, test=0.318), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.749, test=0.262), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.828, test=0.185), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.892, test=0.308), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.911, test=0.290), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.911, test=0.290), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.828, test=0.146), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.928, test=0.341), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.892, test=0.404), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.828, test=0.146), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.828, test=0.146), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.204, test=0.202), total=   0.2s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.205, test=0.200), total=   0.2s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.204, test=0.202), total=   0.2s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.201, test=0.208), total=   0.2s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.205, test=0.200), total=   0.3s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.204, test=0.202), total=   0.2s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.205, test=0.200), total=   0.2s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.844, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.832, test=0.394), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.895, test=0.317), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.943, test=0.217), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.966, test=0.392), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.913, test=0.317), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=1.000, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=1.000, test=0.455), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.982, test=0.359), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.165), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.294), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.435), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.170), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.482), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.435), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.482), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.435), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.199), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.349), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.522), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.194), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.542), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.466), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.241), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.542), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.466), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.844, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.832, test=0.394), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.895, test=0.317), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.943, test=0.217), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.966, test=0.392), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.913, test=0.317), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=1.000, test=0.455), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.982, test=0.359), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.165), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.294), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.435), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.170), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.482), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.435), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.482), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.435), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.199), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.349), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.522), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.194), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.542), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.466), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.241), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.542), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.466), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.720, test=0.328), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.558, test=0.318), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.558, test=0.318), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.749, test=0.262), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.828, test=0.185), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.892, test=0.308), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.828, test=0.185), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.875, test=0.308), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.911, test=0.290), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.828, test=0.146), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.928, test=0.341), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.892, test=0.404), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.828, test=0.146), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.828, test=0.146), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.928, test=0.341), total=   0.2s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.720, test=0.328), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.558, test=0.318), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.549, test=0.190), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.558, test=0.318), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.828, test=0.185), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.892, test=0.308), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.875, test=0.308), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.911, test=0.290), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.828, test=0.146), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.928, test=0.341), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.892, test=0.404), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.828, test=0.146), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.928, test=0.341), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.828, test=0.146), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.205, test=0.200), total=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.205, test=0.200), total=   0.2s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gbtree, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.1s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.1s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.1s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.1s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.424, test=0.282), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.385, test=0.286), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.404, test=0.239), total=   0.0s\n",
      "[CV] booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=gblinear, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.424, test=0.308), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.844, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.832, test=0.394), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.895, test=0.317), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.943, test=0.217), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.966, test=0.392), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.913, test=0.317), total=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=1.000, test=0.455), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.982, test=0.359), total=   0.2s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.165), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.294), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.435), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.170), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.482), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.435), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.482), total=   0.2s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.435), total=   0.2s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.199), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.349), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.522), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.194), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.542), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.466), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.241), total=   0.2s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.542), total=   0.2s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.466), total=   0.2s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.844, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.832, test=0.394), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.895, test=0.317), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.943, test=0.217), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.966, test=0.392), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.913, test=0.317), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=1.000, test=0.455), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.982, test=0.359), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.165), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.294), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.435), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.170), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.482), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.435), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.482), total=   0.2s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.435), total=   0.2s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.199), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.349), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.522), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.194), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.542), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.466), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.241), total=   0.2s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.542), total=   0.3s\n",
      "[CV] booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.466), total=   0.2s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.720, test=0.328), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.549, test=0.190), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.558, test=0.318), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.749, test=0.262), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.549, test=0.190), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.558, test=0.318), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.749, test=0.262), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.828, test=0.185), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.892, test=0.308), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.911, test=0.290), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.911, test=0.290), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.875, test=0.308), total=   0.2s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.828, test=0.146), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.928, test=0.341), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.892, test=0.404), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.828, test=0.146), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.828, test=0.146), total=   0.2s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.928, test=0.341), total=   0.2s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.892, test=0.404), total=   0.2s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.720, test=0.328), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.558, test=0.318), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.549, test=0.190), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.558, test=0.318), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.749, test=0.262), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.828, test=0.185), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.892, test=0.308), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.911, test=0.290), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.828, test=0.146), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.928, test=0.341), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.892, test=0.404), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.828, test=0.146), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.828, test=0.146), total=   0.2s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.928, test=0.341), total=   0.2s\n",
      "[CV] booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.892, test=0.404), total=   0.2s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.201, test=0.208), total=   0.2s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.204, test=0.202), total=   0.2s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.201, test=0.208), total=   0.2s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.1, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.205, test=0.200), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.844, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.832, test=0.394), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.895, test=0.317), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.943, test=0.217), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.966, test=0.392), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.913, test=0.317), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=1.000, test=0.200), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=1.000, test=0.455), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.982, test=0.359), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.165), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.294), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.435), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.170), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.482), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.435), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.200), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.482), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.435), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.199), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.349), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.522), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.194), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.542), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.466), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.241), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.542), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.466), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.844, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.832, test=0.394), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.895, test=0.317), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.943, test=0.217), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.966, test=0.392), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.913, test=0.317), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=1.000, test=0.455), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.982, test=0.359), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.165), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.294), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.435), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.170), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.482), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.435), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.482), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.435), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.199), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.349), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.522), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.194), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.542), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.466), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.241), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.542), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.466), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.720, test=0.328), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.558, test=0.318), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.549, test=0.190), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.558, test=0.318), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.749, test=0.262), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.828, test=0.185), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.892, test=0.308), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.911, test=0.290), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.911, test=0.290), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.828, test=0.146), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.928, test=0.341), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.892, test=0.404), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.828, test=0.146), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.928, test=0.341), total=   0.3s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.892, test=0.404), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.828, test=0.146), total=   0.4s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.928, test=0.341), total=   0.3s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.892, test=0.404), total=   0.4s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.720, test=0.328), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.549, test=0.190), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.558, test=0.318), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.549, test=0.190), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.558, test=0.318), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.749, test=0.262), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.828, test=0.185), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.892, test=0.308), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.828, test=0.185), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.911, test=0.290), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.828, test=0.185), total=   0.5s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.911, test=0.290), total=   0.4s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.875, test=0.308), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.828, test=0.146), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.928, test=0.341), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.828, test=0.146), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.828, test=0.146), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.928, test=0.341), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.892, test=0.404), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.204, test=0.202), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.204, test=0.202), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.201, test=0.208), total=   0.4s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.205, test=0.200), total=   0.5s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.201, test=0.208), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.204, test=0.202), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.201, test=0.208), total=   0.2s\n",
      "[CV] booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.3, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.844, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.832, test=0.394), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.895, test=0.317), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.943, test=0.217), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.966, test=0.392), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.913, test=0.317), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=1.000, test=0.455), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.982, test=0.359), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.165), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.294), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.435), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.170), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.482), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.435), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.482), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.435), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.199), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.349), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.522), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.194), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.542), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.466), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.241), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.542), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.466), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.844, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.832, test=0.394), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.895, test=0.317), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.943, test=0.217), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.966, test=0.392), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.913, test=0.317), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=1.000, test=0.455), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.982, test=0.359), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.165), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.294), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.435), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.170), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.482), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.435), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.200), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.482), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.435), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.199), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.349), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.522), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.194), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.542), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.466), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.241), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.542), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=dart, eta=0.6, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.466), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.720, test=0.328), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.558, test=0.318), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.549, test=0.190), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.558, test=0.318), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.749, test=0.262), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.828, test=0.185), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.892, test=0.308), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.911, test=0.290), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.911, test=0.290), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.875, test=0.308), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.828, test=0.146), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.928, test=0.341), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.828, test=0.146), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.828, test=0.146), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.928, test=0.341), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.892, test=0.404), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.720, test=0.328), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.549, test=0.190), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.558, test=0.318), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.549, test=0.190), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.558, test=0.318), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.749, test=0.262), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.828, test=0.185), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.892, test=0.308), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.911, test=0.290), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.828, test=0.185), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.911, test=0.290), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.875, test=0.308), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.828, test=0.146), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.928, test=0.341), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.828, test=0.146), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.828, test=0.146), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.928, test=0.341), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.892, test=0.404), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.205, test=0.200), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.201, test=0.208), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.201, test=0.208), total=   0.4s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.205, test=0.200), total=   0.2s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.6, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.844, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.832, test=0.394), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.895, test=0.317), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.943, test=0.217), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.966, test=0.392), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.913, test=0.317), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=1.000, test=0.455), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.982, test=0.359), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.165), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.294), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=1.000, test=0.435), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.170), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.482), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=1.000, test=0.435), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.482), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=1.000, test=0.435), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.199), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.349), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=1.000, test=0.522), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.194), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.542), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=1.000, test=0.466), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.241), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.542), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=1.000, test=0.466), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.844, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.832, test=0.394), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.895, test=0.317), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.943, test=0.217), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.966, test=0.392), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.913, test=0.317), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=1.000, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=1.000, test=0.455), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.982, test=0.359), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.165), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.294), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=1.000, test=0.435), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.170), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.482), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=1.000, test=0.435), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.200), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.482), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=1.000, test=0.435), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.199), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.349), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=1.000, test=0.522), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.194), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.542), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=1.000, test=0.466), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.241), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.542), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=0, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=1.000, test=0.466), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.720, test=0.328), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.549, test=0.190), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.558, test=0.318), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.549, test=0.190), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.558, test=0.318), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.749, test=0.262), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.828, test=0.185), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.892, test=0.308), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.911, test=0.290), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.828, test=0.185), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.911, test=0.290), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.828, test=0.146), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.828, test=0.146), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.828, test=0.146), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.928, test=0.341), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.892, test=0.404), total=   0.4s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.720, test=0.328), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.549, test=0.190), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.558, test=0.318), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.749, test=0.262), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.549, test=0.190), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.558, test=0.318), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.749, test=0.262), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.828, test=0.185), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.911, test=0.290), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.892, test=0.308), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.828, test=0.185), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.911, test=0.290), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.875, test=0.308), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.828, test=0.185), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.911, test=0.290), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.875, test=0.308), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.828, test=0.146), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.928, test=0.341), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.892, test=0.404), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.828, test=0.146), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.892, test=0.404), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.828, test=0.146), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.928, test=0.341), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=1, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.892, test=0.404), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=100, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=1, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=100, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=3, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=depthwise, max_depth=6, n_estimators=200, score=(train=0.205, test=0.200), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=100, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=1, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.201, test=0.208), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=3, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.204, test=0.202), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.201, test=0.208), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=50, score=(train=0.205, test=0.200), total=   0.0s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.201, test=0.208), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=100, score=(train=0.205, test=0.200), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.204, test=0.202), total=   0.1s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.201, test=0.208), total=   0.2s\n",
      "[CV] booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200 \n",
      "[CV]  booster=dart, eta=0.9, gamma=10, grow_policy=lossguide, max_depth=6, n_estimators=200, score=(train=0.205, test=0.200), total=   0.1s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=1)]: Done 1944 out of 1944 | elapsed:  1.9min finished\n",
      "C:\\Users\\72445\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\sklearn\\model_selection\\_search.py:813: DeprecationWarning: The default of the `iid` parameter will change from True to False in version 0.22 and will be removed in 0.24. This will change numeric results when test-set sizes are unequal.\n",
      "  DeprecationWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=3, error_score='raise-deprecating',\n",
       "             estimator=XGBClassifier(base_score=0.5, booster='gbtree',\n",
       "                                     colsample_bylevel=1, colsample_bynode=1,\n",
       "                                     colsample_bytree=1, gamma=0,\n",
       "                                     learning_rate=0.1, max_delta_step=0,\n",
       "                                     max_depth=3, min_child_weight=1,\n",
       "                                     missing=None, n_estimators=100, n_jobs=1,\n",
       "                                     nthread=None, objective='multi:softprob',\n",
       "                                     random_state=0, reg_alpha=0, reg_la...\n",
       "                                     scale_pos_weight=1, seed=None, silent=None,\n",
       "                                     subsample=1, verbosity=1),\n",
       "             iid='warn', n_jobs=None,\n",
       "             param_grid={'booster': ['gbtree', 'gblinear', 'dart'],\n",
       "                         'eta': [0.1, 0.3, 0.6, 0.9], 'gamma': [0, 1, 10],\n",
       "                         'grow_policy': ['depthwise', 'lossguide'],\n",
       "                         'max_depth': [1, 3, 6],\n",
       "                         'n_estimators': [50, 100, 200]},\n",
       "             pre_dispatch='2*n_jobs', refit=True, return_train_score=True,\n",
       "             scoring='f1_macro', verbose=5)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "search = GridSearchCV(clf, params, cv=3, return_train_score=True, verbose=5, scoring='f1_macro')\n",
    "\n",
    "search.fit(X,y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Tuned Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Training Score: 0.5742668682018693\n",
      "Mean Testing Score: 1.0\n",
      "\n",
      "Best Parameter Found:\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'booster': 'gbtree',\n",
       " 'eta': 0.1,\n",
       " 'gamma': 0,\n",
       " 'grow_policy': 'depthwise',\n",
       " 'max_depth': 6,\n",
       " 'n_estimators': 200}"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Mean Training Score:\", np.mean(search.cv_results_['mean_train_score']))\n",
    "print(\"Mean Testing Score:\", search.score(X, y))\n",
    "print(\"\\nBest Parameter Found:\")\n",
    "search.best_params_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model with the Best Parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n",
       "              colsample_bynode=1, colsample_bytree=1, eta=0.1, gamma=0,\n",
       "              grow_policy='depthwise', learning_rate=0.1, max_delta_step=0,\n",
       "              max_depth=6, min_child_weight=1, missing=None, n_estimators=200,\n",
       "              n_jobs=1, nthread=None, objective='multi:softprob',\n",
       "              random_state=0, reg_alpha=0, reg_lambda=1, scale_pos_weight=1,\n",
       "              seed=None, silent=None, subsample=1, verbosity=1)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "search_clf = search.best_estimator_\n",
    "\n",
    "search_clf.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Results from Optimum Parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "        Sell       0.20      0.20      0.20         5\n",
      "         Buy       0.64      0.70      0.67        10\n",
      "        Hold       0.00      0.00      0.00         2\n",
      "\n",
      "    accuracy                           0.47        17\n",
      "   macro avg       0.28      0.30      0.29        17\n",
      "weighted avg       0.43      0.47      0.45        17\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Classifier predictions\n",
    "s_pred = search_clf.predict(X_test)\n",
    "\n",
    "#Printing out results\n",
    "report = classification_report(y_test, s_pred, target_names=['Sell', 'Buy', 'Hold'])\n",
    "print(report)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Confusion Matrix for Optimum Parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_confusion_matrix(y_test, s_pred, title=\"Confusion Matrix\")\n",
    "np.set_printoptions(precision=1)\n",
    "# Plot non-normalized confusion matrix\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
